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TensorFlow 1.x Deep Learning Cookbook

You're reading from TensorFlow 1.x Deep Learning Cookbook Over 90 unique recipes to solve artificial-intelligence driven problems with Python

Product type Paperback

Published in Dec 2017

Publisher Packt

ISBN-13 9781788293594

Length 536 pages

Edition 1st Edition

Languages

Python

Tools

TensorFlow

Concepts

Deep Learning

Authors (2):

Dr. Amita Kapoor

Antonio Gulli

View More author details

Table of Contents (15) Chapters

Preface

1. TensorFlow - An Introduction

2. Regression FREE CHAPTER

3. Neural Networks - Perceptron

4. Convolutional Neural Networks

5. Advanced Convolutional Neural Networks

6. Recurrent Neural Networks

7. Unsupervised Learning

8. Autoencoders

9. Reinforcement Learning

10. Mobile Computation

11. Generative Models and CapsNet

12. Distributed TensorFlow and Cloud Deep Learning

13. Learning to Learn with AutoML (Meta-Learning)

14. TensorFlow Processing Units

Components of TPUs

Running Distributed TensorFlow on Amazon AWS

Amazon AWS offers P2.x machine featuring NVIDIA K8 GPU. To be able to use, again the first step involves creating an Amazon AWS account. If you do not have one already, you can create it using the link: https://portal.aws.amazon.com/billing/signup?nc2=h_ct&redirect_url=https%3A%2F%2Faws.amazon.com%2Fregistration-confirmation#/start . Once you login into your account, your dashboard looks like this:

You can see that Amazon AWS provides a host of services, but here we are concerned with using Amazon AWS for Deep learning.

The GPUs are available only in P2 instance creation, and are not available by default, to get this service one has to raise a ticket for increasing resources via AWS support, the support is available in the top right corner, once you go to support, you will see a button Create case, choose the button and make following...

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